Create ML Models with BigQuery ML: Challenge Lab Reviews

Maximillian Jonathan P. · Reviewed 1 yıldan fazla ago

David L. · Reviewed 1 yıldan fazla ago

Ulu Kagan B. · Reviewed 1 yıldan fazla ago

Rupali P. · Reviewed 1 yıldan fazla ago

Siddhartha G. · Reviewed 1 yıldan fazla ago

Thangaraj S. · Reviewed 1 yıldan fazla ago

Nigel Malino N. · Reviewed 1 yıldan fazla ago

Sandy W. · Reviewed 1 yıldan fazla ago

FRANCISCO JAVIER S. · Reviewed 1 yıldan fazla ago

Narayana V. · Reviewed 1 yıldan fazla ago

Andre G. · Reviewed 1 yıldan fazla ago

Edgar D. · Reviewed 1 yıldan fazla ago

damien c. · Reviewed 1 yıldan fazla ago

Patricia M. · Reviewed 1 yıldan fazla ago

good

Samrat N. · Reviewed 1 yıldan fazla ago

Caio G. · Reviewed 1 yıldan fazla ago

Patrick J. · Reviewed 1 yıldan fazla ago

Srijan M. · Reviewed 1 yıldan fazla ago

Srijan M. · Reviewed 1 yıldan fazla ago

Christian O. · Reviewed 1 yıldan fazla ago

Brian shahputera s. · Reviewed 1 yıldan fazla ago

I had to use my head a little bit and I got a good feel of how I can use sql(BigQuery) to evaluate ML models on a dataset. I see that it can get very complex very fast. Thanks for keeping it simple. The lab has a nice UI and just the right amount of complexitity to test the system.

웅비 최. · Reviewed 1 yıldan fazla ago

Kalman T. · Reviewed 1 yıldan fazla ago

I found Task 4 of this lab to be misleading and frustrating. The instructions explicitly state that I need to "predict the average trip duration for all trips from the busiest bike sharing station in 2019 (based on the number of trips per station in 2019)." Based on these instructions, I wrote queries to: Calculate the busiest station in 2019 based on trip count Use that station to make predictions with the subscriber_type model Filter for Single Trip subscribers and 2019 data Calculate the average predicted duration However, the verification system would only accept a query that used a hardcoded station name '21st & Speedway @PCL', which is never mentioned anywhere in the instructions. This is problematic because: The instructions specifically tell us to base our solution on 2019 trip counts There's no indication we should use a pre-defined station The verification system contradicts the written instructions Students waste time trying to debug technically correct solutions A better approach would be to either: a) Update the instructions to specify using '21st & Speedway @PCL' if that's the required solution b) Or modify the verification system to accept solutions that correctly calculate and use the actual busiest station from 2019 data This discrepancy between instructions and verification criteria creates unnecessary confusion and doesn't reflect real-world data analysis practices where we would actually want to calculate the busiest station rather than assuming it.

Anshul K. · Reviewed 1 yıldan fazla ago

Boone H. · Reviewed 1 yıldan fazla ago